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Chilled meat has a high water activity and is rich in nutrients, so it is prone to microbial contamination during industrial production, and the microorganisms contaminated are widespread and complex. In order to address its biosafety issues and potential food safety risks, the experiment was conducted to investigate the variation of dominant spoilage bacteria in chilled meat under storage conditions of 2 ± 2 ℃, 10 ± 2 ℃, and 20 ± 2 ℃, respectively. At the same time, the variation of spoilage bacteria in four layers of chilled meat under three temperature conditions was detected. The results showed that when chilled pork was stored at 2 ± 2 ℃ and 10 ± 2 ℃, Pseudomonas sp., Thermosporaceae, and Enterobacteriaceae were the dominant spoilage bacteria in chilled pork, while when stored at 20 ± 2 ℃, Thermosporaceae, Enterobacteriaceae, Pseudomonas sp., and Lactobacillus sp. became the dominant spoilage bacteria in chilled pork; When chilled pork was stored at 2 ± 2 ℃ and 10 ± 2 ℃, the order of proliferation of different types of spoilage microorganisms in the inner layer was as follows: Fusarium thermophila>Enterobacteriaceae>Lactobacillus>Pseudomonas>Yeast/Yeast>Staphylococcus/ Micrococcus; When stored at 20 ± 2 ℃, the order of the number of proliferation of different types of spoilage microorganisms is as follows: Thermomycetes>Enterobacteriaceae>Lactobacillus >Yeast/Yeast>Pseudomonas>Staphylococcus/Micrococcus. Finally, through the change rules of dominant spoilage bacteria under three temperatures and the penetration of spoilage bacteria in chilled meat, it provides a theoretical basis for enterprises to improve precision sterilization and key control point technology.

Salmonella infections in eggs with increasing morbidity and mortality exhibit worldwide prevalence. The present study intends to evaluate the efficacy of Lactobacillus reuteri Lb11 (L. reuteri Lb11, isolated from chicken intestinal tract) in inhibiting the growth of multi-drug resistant (MDR) Salmonella Enteritidis SE05 (obtained from egg content). The cell-free cell lysates (CFCL) of L. reuteri Lb11 obtained by the agar spot test performed well on inhibition of the MDR (Multi-Drug Resistant) Salmonella Enteritidis SE05, The heat-inactivated (HI) fraction of L. reuteri Lb11 showed no inhibition activity. By co-culturing with L. reuteri Lb11 in vitro, the growth of S. Enteritidis SE05 decreased along with time, while, the pH value decreased significantly. Furthermore, In order to evaluate the mechanism of action of CFCL of L.reuteri Lb11, the genes related to the transcription level of AcrAB-TolC efflux pump, outer membrane protein OMPs genes and drug resistance genes have been quantified by real-time PCR, when the S. Enteritidis was SE05 exposed to the CFCL of L. reuteri Lb11 (1 × 1012 CFU/mL). Almost all of the AcrAB-TolC efflux pump genes, outer membrane protein genes and antibiotic resistance genes were down-regulated. Especially, the level of ramA, tetA and tetB genes were down-regulated -20.77, -15.85 and -12.42 folds, respectively. L. reuteri Lb11 can effectively prevent the formation of efflux pump to inhibit the production of multidrug-resistant Salmonella Enteritidis in eggs.

Lactic Acid Bacteria (LAB) regulate and maintain the stability of healthy microbial flora, inhibit the adhesion of pathogenic bacteria and promote the colonization of beneficial micro-organisms. The drug resistance and pathogenicity of Salmonella enteritis SE47 isolated from retail eggs were investigated. Meanwhile, Enterococcus faecalis L76 and Lactobacillus salivarius LAB35 were isolated from intestine of chicken. With SE47 as indicator bacteria, the diameters of L76 and LAB35 inhibition zones were 12 mm and 8·5 mm, respectively, by agar inhibition circle method, which indicated that both of them had inhibitory effect on Salmonella, and L76 had better antibacterial effect; two chicken-derived lactic acid bacteria isolates and Salmonella SE47 were incubated with Caco-2. The adhesion index of L76 was 17·5%, which was much higher than that of LAB35 (10·21%) and SE47 (4·89%), this experiment shows that the higher the bacteriostatic effect of potential probiotics, the stronger the adhesion ability; then Caco-2 cells were incubated with different bacteria, and the survival of Caco-2 cells was observed by flow cytometry. Compared with Salmonella SE47, the results showed that lactic acid bacteria isolates could effectively protect Caco-2 cells; finally, after different bacteria incubated Caco-2 cells, according to the cytokine detection kit, the RNA of Caco-2 cells was extracted and transcribed into cDNA, then detected by fluorescence quantitative PCR, the results showed that L76 could protect Caco-2 cells from the invasion of Salmonella SE47, with less cell membrane rupture and lower expression of MIF and TNF genes. Therefore, the lactic acid bacteria isolates can effectively inhibit the adhesion of Salmonella and protect the integrity of intestinal barrier.

The high moisture and nutrient contents of spiced beef make it popular with consumers but present challenges for its storage, as spoilage is a common phenomenon. Therefore, for identifying packaging methods to reduce spoilage during storage, this study investigated the effects of 5% O2 (low oxygen), 70% CO2 (high carbon dioxide), and 5% O2/70% CO2/25% N2 (compound group) on lipid oxidation in spiced beef in the test groups and a vacuum‐packed group (control) at storage temperatures of 4, 25, and 60°C. The pH, thiobarbituric acid (TBA), anisidine value (AV), and peroxide value (POV) of the spiced beef were determined. Results indicated that 70% CO2 and storage at 4 and 25°C showed the strongest ability to inhibit the rancidity in spiced beef. The 5% O2 group delayed both initial oxidation and secondary oxidation of lipids. Although the compound group significantly inhibited the rancidity in spiced beef at 60°C, it could not maintain such inhibition for long. Among all the groups, the 70% CO2 group demonstrated maximum inhibition of initial lipid oxidation and suppressed the secondary oxidation of lipids for the longest time. Thus, the modified atmosphere packaging with O2 and CO2 can regulate the fat oxidation in meat products and effectively improve their flavor maintenance., Spiced beef is a traditional Chinese cooked food product, and research on the mechanism of lipid oxidation of spiced beef in foreign countries is lacking. Atmosphere packaging technology was used for the first time for the preservation of traditional Chinese spiced beef. The effect of single gas component (5% O2/95% N2, 70% CO2/30% N2) on lipid oxidation of spiced beef was studied.

S. enterica is an important foodborne pathogen worldwide. As some strains can form biofilms which may offer protection against antimicrobials, it is of interest to explore ways to prevent biofilm formation by S. enterica. In this study, we engineered a short β-sheet peptide WK2 (WKWKCTKSGCKWKW-NH2) and examined its antimicrobial and anti-biofilm activities against various S. enterica strains, including the multidrug-resistant S. Typhimurium DT104. WK2 displayed bacteriostatic activity with a geometric mean (GM) minimum inhibitory concentration (MIC) of 4.17 μg/mL, and bactericidal activity, with a GM lethal concentration (LC) of 7.51 μg/mL. Crystal violet staining and fluorescence measurements demonstrated that WK2 inhibited S. Typhimurium DT104 biofilm formation at 0.5 μg/mL and killed the sessile cells in biofilms at 8 μg/mL. Real-time polymerase chain reaction (qPCR) and microscopic observation revealed that the anti-biofilm activity of WK2 likely arises through the formation of complexes with bacterial DNA, inhibition of surface organelle biosynthesis and interference with autoinducer-2 (AI-2)-mediated quorum sensing (QS). Therefore, WK2 is a promising antimicrobial agent for the prevention and control of biofilms produced by multidrug-resistant S. enterica.

Salmonella is considered one of the most important foodborne pathogens and is commonly associated with the consumption of eggs, chicken meat, chicken intestines and other animal products. Multidrug resistant (MDR) Salmonella strains are highly adaptive and have been responsible for several foodborne disease outbreaks. We investigated the genetic relatedness, antibiotic resistance and virulence genes of 160 strains which were recovered from 920 samples. The samples were collected from the chicken intestines and eggs in their environment, in the wet markets and chicken farm in Jiang Su province of China. Of the total 920 samples analysed, 160 (17.4%) were positive for Salmonella. 61 (61/440) strains were detected in egg samples and 99 (99/480) strains detected in chicken intestine samples. The detection rates of Salmonella were different in different months and at different sampling sites. The resistance of 160 Salmonella strains to 16 antibiotics was detected by the agar disk diffusion method. The isolates from chicken intestines and eggs were more resistant to sulfamethoxazole (SMZ), ceftriaxone (CRO), nalidixic acid (NAL), cefazolin (CFZ), and amoxicillin (AMX). In addition, the strains isolated from eggs were relatively resistant to gentamicin (GEN) and kanamycin (KAN), while the strains isolated from chicken intestines were relatively resistant to ciprofloxacin (CIP) and tetracycline (TET). Salmonella strains isolated from eggs were mostly resistant to 2–5 antibiotics, and eight strains were resistant to six or more antibiotics. Salmonella strains isolated from eggs were mostly resistant to 2–5 antibiotics, and eight strains were resistant to six or more antibiotics. Salmonella isolates from chicken intestines were resistant to 3–7 antibiotics, nine strains were resistant to eight or more antibiotics, and only one strain were resistant to 10 antibiotics. Thirty-four strains of multi-drug-resistant Salmonella were tested for 15 kinds of drug resistance genes and 33 virulence genes by Polymerase Chain Reaction (PCR) amplification. Of these, 10 strains had seven or more drug resistance genes and six of them were found to have more than 20 virulence genes. Finally, 10 strains of highly resistant and pathogenic Salmonella were screened out.

This paper presents a method for SLAM in Robot and Wireless Sensor Network (WSN) System using Bayes framework. A mobile robot equipped with sensor measuring the range to WSN nodes by Received Signal Strength Indicator (RSSI) can simultaneously localize itself as well as locate the sensor nodes of WSN. We adopted an algorithm based Rao-Blackwellized Particle Filter (RBPF) to integrate measurements from the different nodes over time while the robot movies in the environment. Each particle contains an estimation robot pose and a set of auxiliary filters estimating the position of sensor nodes, one for each sensor node which had been observed by robot. The auxiliary filter can switch from Particle Filter in the initial stage to EKF in the subsequent stage due to the characteristic of range-only measurement. The experiment proved the efficiency and practicality of the algorithm.

Localization is a fundamental service required by many wireless sensor network applications. We consider a distributed, probabilistic approach, suitable for outdoor systems with inaccurate range measurements. The approach restricts the possible locations of the nodes by using measurements with a mobile robot known its position and neighboring nodes location estimate. We design a two stages distributed localizing algorithm and use Gaussian Sum Filter for integrating the data involving robot and wireless sensor network. The simulation experiment shows that for inaccurate range measurements the probabilistic approach outperforms existing methods.

An improved Particle Filter algorithm is proposed for WSN-aided robot localization. This algorithm introduces node reliability and proposes its expression to realize information fusion among nodes. After having computed node reliability, sensor nodes with high localization, and take effect on updating particles according to their reliability. Furthermore, a novel simulation system for WSN-Robot based on USARSim is developed, which is used to test our algorithm in this paper. The simulation result shows the good performance of the proposed algorithm in precision of robot localization and convergence speed of Particle filter, and the conformity of the simulation system to the requirement of WSN-robot system research.

A new laser scan matching method based on clustering is advanced. It takes the advantages of both non-iterative matching method and iterative matching method as well as increases the speed and the precision of matching. A method of map building based on laser scans using the matching method above is presented for mobile robots. The map building method matches two consecutive scans by using the feature points extracted from the scans and then completes the whole map building. In the experiment using the rescue robot developed in our lab, it shows that the new method can accomplish the task of real-time map building in an indoor environment accurately and effectively.

One of the challenges of SLAM (simultaneous localization and mapping) for autonomous robots is the loop closing problem. In this paper, a decision-theoretic active loop closing approach is presented, which integrates the exploration planning with loop closing. In our approach, the active loop closing process is modeled as a multi-stage decision problem, and a frontier-based auxiliary topological map is build to assist the decision process. The autonomous robot chooses its actions according to the sequential decision results. The unknown range most likely to close a loop is selected to explored, and a particle-filter-based localization and smoothing method applied to partial maps is used in the loop validating and loop constraint building process. Experiments have shown that our approach can practically implement loop closure and obviously improve the mapping precision compared to passive exploration strategy.

This paper illustrates the reason why revisable data association is needed for the simultaneous localization and mapping (SLAM) of mobile robots, and an incremental SLAM algorithm with backtrack searching data association is presented. Our approach uses a tree model called correspondence tree (CT) to represent the solution space of the data association problem. CT is layered according to time steps and every node in it is a data association hypothesis for the measurements gotten at-a-time. A best-first with limit backtracking search strategy is designed to find the optimal path in CT. A state estimation method based on the least-squares problem is developed. This method can compute the cost of nodes in CT and update state estimation incrementally, so direct feedback is introduced from the state estimation process to the data association model. With the interaction between data association and state estimation, and combining with tree pruning techniques, our approach can get accurate data association and state estimation for online SLAM applications. The contribution of this paper is that we have analyzed the necessity of revisable data association for SLAM and we use graph search of AI to model and solve the revising data association problem.

This paper focuses on the reciprocity between data association and state estimation in the simultaneous localization and mapping (SLAM) problem for mobile robot, and an incremental SLAM algorithm with backtracking data association is presented. Our approach uses a tree model called correspondence tree (CT) to represent the solution space of the data association problem. CT is layered according to time steps and every node in it is a data association hypothesis for the measurements gotten at a time. A best-first with limit backtracking search strategy is designed to find the optimal path in CT. A state estimation method based on the least-squares problem is developed. This method can compute the cost of nodes in CT and update state estimation incrementally, so direct feedback is introduced from the state estimation process to the data association model. With the interaction between data association and state estimation, and combining with tree pruning techniques, our approach can get accurate data association and state estimation for on-line SLAM applications.